System and method for automatically detecting and initiating a walk

ABSTRACT

Systems, methods, and apparatuses for detecting the start of a walk event are disclosed. The method comprises detecting that a wearable device is in a walk mode if it is determined that the wearable device has exited a geo-fence zone and that the wearable device is not connected to a wireless network; comparing current environment details associated with the wearable device to past walk environment details associated with the wearable device to identify at least one similarity between the current environment details and the past walk environment details; confirming that the wearable device is in the walk mode upon identifying at least one similarity between the current environment details and the past walk environment details, the predictive function refined using the one or more previous responses to a walk mode prompt; and transmitting a recorded GPS location of the wearable device while the wearable device is in a walk mode.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/291,882, filed Oct. 12, 2016.

COPYRIGHT NOTICE

This application includes material that may be subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent disclosure, as it appears in thePatent and Trademark Office files or records, but otherwise reserves allcopyright rights whatsoever

BACKGROUND

The embodiments described in the disclosure relate to the field ofactivity or location-based tracking and specifically, to automaticallydetecting the start of a walk event of a wearable tracking device.

Human users are increasingly using wearable devices to utilize numerouscomputing functions provided by a conveniently sized device. Frequently,wearable devices are utilized to measure and track human activity tomaintain a healthy lifestyle and monitor progress towards specificfitness goals.

Recently, wearable devices have been created to monitor and analyze themovement and activity of non-human wearers, such as household pets.Wearable devices placed on household pets also allow for the monitoringof movement and activity and allow for the tracking of household petswhile owners are not present.

Frequently however, household pets exhibit a significant amount ofinertia and lack the ability to manually (and intentionally) control awearable device. Thus, current wearable devices designed for animalsrequire constant GPS monitoring to track the location and activity ofthe animals despite the relative level of inactivity of the animal. Suchconstant monitoring is required as the wearable device has no way tointelligently determine when GPS tracking is required and when it is notrequired.

Constant use of GPS receivers significantly impacts the battery life ofa wearable device and thus require the device to be rechargedfrequently, often every day or multiple times per day. Moreover,constant GPS polling (and transmittal to a server) requires significantbandwidth expenditures that, depending on the network use, may be bothcostly and impractical. Further, given the relatively long periods ofinactivity, the collection of GPS data at all times for animals isunnecessary. Instead, GPS data is only needed during relatively briefperiods of an animal's day.

Thus, there exists a need in the art for a system, device, and methodfor intelligently monitoring the location of a wearable device anddetermining when elevated GPS monitoring is required based on theactivity of the wearable device.

BRIEF SUMMARY

To remedy the aforementioned deficiencies, the disclosure presentssystems, methods, and apparatuses for automatically monitoring thelocation of a wearable device and selecting enabling GPS tracking ofsaid device in response to the determination that the device is engagingin a walk activity.

In one embodiment, the disclosure describes a method for detecting thestart of a walk event. The method includes identifying the location of awearable device; determining if the wearable device has exited ageo-fence zone; confirming that a wearable device is in a walk mode ifit is determined that the wearable device has exited a geo-fence zoneand that the wearable device is not connected to a wireless network;enabling a GPS receiver; continuously recording the location of thewearable device received from the GPS receiver while the wearable deviceis in a walk mode; and transmitting the recorded location of thewearable device while the wearable device is in a walk mode.

In one embodiment, the disclosure describes an apparatus for detectingthe start of a walk event. The apparatus includes a processor, GPSreceiver, and a non-transitory memory storing computer-executableinstructions therein that, when executed by the processor. Thecomputer-executable instructions cause the apparatus to identify thelocation of a wearable device; determine if the wearable device hasexited a geo-fence zone; confirm that a wearable device is in a walkmode if it is determined that the wearable device has exited a geo-fencezone and that the wearable device is not connected to a wirelessnetwork; enable the GPS receiver; continuously record the location ofthe wearable device received from the GPS receiver while the wearabledevice is in a walk mode; and transmit the recorded location of thewearable device while the wearable device is in a walk mode.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of thedisclosure will be apparent from the following description ofembodiments as illustrated in the accompanying drawings, in whichreference characters refer to the same parts throughout the variousviews. The drawings are not necessarily to scale, emphasis instead beingplaced upon illustrating principles of the disclosure:

FIG. 1 is a network diagram illustrating a system for detecting thestart of a walk event according to some embodiments of the disclosure;

FIG. 2 is a physical diagram illustrating a tracking device fordetecting the start of a walk event according to some embodiments of thedisclosure;

FIG. 3 is a logical block diagram illustrating a tracking device fordetecting the start of a walk event according to some embodiments of thedisclosure;

FIG. 4 is a flow diagram illustrating a method for detecting the startof a walk event according to some embodiments of the disclosure; and

FIG. 5 is a flow diagram illustrating a method for confirming the startof a walk event according to some embodiments of the disclosure.

DETAILED DESCRIPTION

The present disclosure will now be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, certain example embodiments. Subjectmatter may, however, be embodied in a variety of different forms and,therefore, covered or claimed subject matter is intended to be construedas not being limited to any example embodiments set forth herein;example embodiments are provided merely to be illustrative. Likewise, areasonably broad scope for claimed or covered subject matter isintended. Among other things, for example, subject matter may beembodied as methods, devices, components, or systems. Accordingly,embodiments may, for example, take the form of hardware, software,firmware or any combination thereof (other than software per se). Thefollowing detailed description is, therefore, not intended to be takenin a limiting sense.

Throughout the specification and claims, terms may have nuanced meaningssuggested or implied in context beyond an explicitly stated meaning.Likewise, the phrase “in one embodiment” as used herein does notnecessarily refer to the same embodiment and the phrase “in anotherembodiment” as used herein does not necessarily refer to a differentembodiment. It is intended, for example, that claimed subject matterinclude combinations of example embodiments in whole or in part.

In general, terminology may be understood at least in part from usage incontext. For example, terms, such as “and”, “or”, or “and/or,” as usedherein may include a variety of meanings that may depend at least inpart upon the context in which such terms are used. Typically, “or” ifused to associate a list, such as A, B or C, is intended to mean A, B,and C, here used in the inclusive sense, as well as A, B or C, here usedin the exclusive sense. In addition, the term “one or more” as usedherein, depending at least in part upon context, may be used to describeany feature, structure, or characteristic in a singular sense or may beused to describe combinations of features, structures or characteristicsin a plural sense. Similarly, terms, such as “a,” “an,” or “the,” again,may be understood to convey a singular usage or to convey a pluralusage, depending at least in part upon context. In addition, the term“based on” may be understood as not necessarily intended to convey anexclusive set of factors and may, instead, allow for existence ofadditional factors not necessarily expressly described, again, dependingat least in part on context.

The present disclosure is described below with reference to blockdiagrams and operational illustrations of methods and devices. It isunderstood that each block of the block diagrams or operationalillustrations, and combinations of blocks in the block diagrams oroperational illustrations, can be implemented by means of analog ordigital hardware and computer program instructions. These computerprogram instructions can be provided to a processor of a general-purposecomputer to alter its function as detailed herein, a special purposecomputer, ASIC, or other programmable data processing apparatus, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, implement thefunctions/acts specified in the block diagrams or operational block orblocks. In some alternate implementations, the functions/acts noted inthe blocks can occur out of the order noted in the operationalillustrations. For example, two blocks shown in succession can in factbe executed substantially concurrently or the blocks can sometimes beexecuted in the reverse order, depending upon the functionality/actsinvolved.

These computer program instructions can be provided to a processor of: ageneral purpose computer to alter its function to a special purpose; aspecial purpose computer; ASIC; or other programmable digital dataprocessing apparatus, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, implement the functions/acts specified in the block diagramsor operational block or blocks, thereby transforming their functionalityin accordance with embodiments herein.

For the purposes of this disclosure a computer readable medium (orcomputer-readable storage medium/media) stores computer data, which datacan include computer program code (or computer-executable instructions)that is executable by a computer, in machine readable form. By way ofexample, and not limitation, a computer readable medium may comprisecomputer readable storage media, for tangible or fixed storage of data,or communication media for transient interpretation of code-containingsignals. Computer readable storage media, as used herein, refers tophysical or tangible storage (as opposed to signals) and includeswithout limitation volatile and non-volatile, removable andnon-removable media implemented in any method or technology for thetangible storage of information such as computer-readable instructions,data structures, program modules or other data. Computer readablestorage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM,flash memory or other solid-state memory technology, CD-ROM, DVD, orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other physical ormaterial medium which can be used to tangibly store the desiredinformation or data or instructions and which can be accessed by acomputer or processor.

For the purposes of this disclosure the term “server” should beunderstood to refer to a service point which provides processing,database, and communication facilities. By way of example, and notlimitation, the term “server” can refer to a single, physical processorwith associated communications and data storage and database facilities,or it can refer to a networked or clustered complex of processors andassociated network and storage devices, as well as operating softwareand one or more database systems and application software that supportthe services provided by the server. Servers may vary widely inconfiguration or capabilities, but generally a server may include one ormore central processing units and memory. A server may also include oneor more mass storage devices, one or more power supplies, one or morewired or wireless network interfaces, one or more input/outputinterfaces, or one or more operating systems, such as Windows Server,Mac OS X, Unix, Linux, FreeBSD, or the like.

For the purposes of this disclosure a “network” should be understood torefer to a network that may couple devices so that communications may beexchanged, such as between a server and a client device or other typesof devices, including between wireless devices coupled via a wirelessnetwork, for example. A network may also include mass storage, such asnetwork attached storage (NAS), a storage area network (SAN), or otherforms of computer or machine-readable media, for example. A network mayinclude the Internet, one or more local area networks (LANs), one ormore wide area networks (WANs), wire-line type connections, wirelesstype connections, cellular or any combination thereof. Likewise,sub-networks, which may employ differing architectures or may becompliant or compatible with differing protocols, may interoperatewithin a larger network. Various types of devices may, for example, bemade available to provide an interoperable capability for differingarchitectures or protocols. As one illustrative example, a router mayprovide a link between otherwise separate and independent LANs.

A communication link or channel may include, for example, analogtelephone lines, such as a twisted wire pair, a coaxial cable, full orfractional digital lines including T1, T2, T3, or T4 type lines,Integrated Services Digital Networks (ISDNs), Digital Subscriber Lines(DSLs), wireless links including satellite links, or other communicationlinks or channels, such as may be known to those skilled in the art.Furthermore, a computing device or other related electronic devices maybe remotely coupled to a network, such as via a wired or wireless lineor link, for example.

For purposes of this disclosure, a “wireless network” should beunderstood to couple client devices with a network. A wireless networkmay employ stand-alone ad-hoc networks, mesh networks, Wireless LAN(WLAN) networks, cellular networks, or the like. A wireless network mayfurther include a system of terminals, gateways, routers, or the likecoupled by wireless radio links, or the like, which may move freely,randomly or organize themselves arbitrarily, such that network topologymay change, at times even rapidly.

A wireless network may further employ a plurality of network accesstechnologies, including Wi-Fi, Long Term Evolution (LTE), WLAN, WirelessRouter (WR) mesh, or 2nd, 3rd, or 4th generation (2G, 3G, or 4G)cellular technology, or the like. Network access technologies may enablewide area coverage for devices, such as client devices with varyingdegrees of mobility, for example.

For example, a network may enable RF or wireless type communication viaone or more network access technologies, such as Global System forMobile communication (GSM), Universal Mobile Telecommunications System(UMTS), General Packet Radio Services (GPRS), Enhanced Data GSMEnvironment (EDGE), 3GPP Long Term Evolution (LTE), LTE Advanced,Wideband Code Division Multiple Access (WCDMA), Bluetooth, 802.11b/g/n,or the like. A wireless network may include virtually any type ofwireless communication mechanism by which signals may be communicatedbetween devices, such as a client device or a computing device, betweenor within a network, or the like.

A computing device may be capable of sending or receiving signals, suchas via a wired or wireless network, or may be capable of processing orstoring signals, such as in memory as physical memory states, and may,therefore, operate as a server. Thus, devices capable of operating as aserver may include, as examples, dedicated rack-mounted servers, desktopcomputers, laptop computers, set top boxes, integrated devices combiningvarious features, such as two or more features of the foregoing devices,or the like. Servers may vary widely in configuration or capabilities,but generally a server may include one or more central processing unitsand memory. A server may also include one or more mass storage devices,one or more power supplies, one or more wired or wireless networkinterfaces, one or more input/output interfaces, or one or moreoperating systems, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, or the like.

FIG. 1 is a network diagram illustrating a system for detecting thestart of a walk event according to some embodiments of the disclosure.As illustrated in FIG. 1, the system 100 includes a tracking device 102,mobile device 104, server 106, and network 108.

As illustrated in FIG. 1, a tracking device 102 may comprise a computingdevice designed to be worn, or otherwise carried, by a user or otherentity, such as an animal. In one embodiment, the tracking device 102may include the hardware illustrated in FIG. 2. The tracking device 102may be configured to collect data generated by various hardwarecomponents present within the tracking device 102, such as GPSreceivers, accelerometers, gyroscopes, or other devices capable ofrecording data regarding the movement or activity of the tracking device102.

As discussed in more detail herein, tracking device 102 may furtherinclude processing logic (e.g., a CPU) capable of receiving andprocessing the motion data. In some embodiments, the tracking device 102may specifically be configured to receive data and pre-process dataprior to transmittal. In addition to recording and processing data,tracking device 102 may further be configured to transmit data,including location and event data, to other devices via network 108.Specific embodiments of processing and transmitting data are describedmore fully with respect to FIGS. 4 through 5.

Although illustrated as a single network, network 108 may comprisemultiple networks facilitating communication between devices. In oneembodiment, the network 108 may include a wireless fidelity (“Wi-Fi”)network as defined by the IEEE 802.11 standards or equivalent standards.In this embodiment, the network 108 may enable the transfer of locationor event data from tracking device 102 to server 106. Additionally, thenetwork 108 may facilitate the transfer of data between tracking device102 and mobile device 104. In an alternative embodiment, the network 108may comprise a mobile network such as a cellular network. In thisembodiment, data may be transferred between the illustrated devices in amanner similar to the embodiment wherein the network 108 is a Wi-Finetwork. Notably, however, if network 108 comprises a mobile network,data transfers may be throttled or subject to interference which reducesthe bandwidth of the network. Finally, in one embodiment, network 108may comprise a Bluetooth network. In this embodiment, tracking device102 and mobile device 104 may be capable of transferring data betweenthemselves. However, server 106 may not be able to communicate withtracking device 102 and mobile device 104. While described in isolation,network 108 may include multiple networks. For example, network 108 mayinclude a Bluetooth network facilitating transfers of data betweentracking device 102 and mobile device 104, a Wi-Fi network, and a mobilenetwork.

The system 100 may further include a mobile device 104. In oneembodiment, a mobile device 104 may include a mobile phone or tabletdevice. In alternative embodiments, the system 100 may additionallyinclude laptop computers, desktop computers, or other personal computingdevices to perform some of the functions described with respect tomobile device 104. As discussed previously, mobile device 104 maycommunicate with a tracking device 102 via a Wi-Fi network or Bluetoothnetwork. In these embodiments, mobile device 104 may receive location orevent data from a tracking device 102 as described in more detailherein. Additionally, tracking device 102 may receive data from mobiledevice 104. In one embodiment, tracking device 102 may receive dataregarding the proximity of mobile device 104 to tracking device 102 oran identification of a user associated with mobile device 104.

Mobile device 104 (or non-mobile device) may additionally communicatewith server 106 to receive data from server 106. For example, server 106may include one or more application servers providing a networkedapplication or application programming interface (API). In oneembodiment, mobile device 104 may be equipped with an application thatcommunicates with server 106 via an API to retrieve and present datawithin the application. In one embodiment, server 106 may providevisualizations of location or event data received from tracking device102. For example, visualization data may include graphs, charts, orother representations of data received from tracking device 102. Anexample of a mobile application that receives data from server 106 isdepicted in FIG. 6.

FIG. 2 is a physical diagram illustrating a tracking device fordetecting the start of a walk event according to some embodiments of thedisclosure. The device 200 includes a CPU 202, memory 204, non-volatilestorage 206, accelerometer 208, GPS receiver 210, cellular transceiver212, Bluetooth transceiver 216, and wireless transceiver 214.

As discussed with respect to FIG. 1, the device 200 may comprise acomputing device designed to be worn, or otherwise carried, by a user orentity such as an animal. The device 200 includes an accelerometer 208and GPS receiver 210 which monitor the device 200 to identify itsposition (via GPS receiver 210) and its acceleration (via accelerometer208). Although illustrated as a single component, accelerometer 208 andGPS receiver 210 may alternatively each include multiple componentsproviding similar functionality.

Accelerometer 208 and GPS receiver 210 generate data as described inmore detail herein and transmits the data to other components via CPU202. Alternatively, or in conjunction with the foregoing, accelerometer208 and GPS receiver 210 may transmit data to memory 204 for short-termstorage. In one embodiment, memory 204 may comprise a random accessmemory device or similar volatile storage device. Alternatively, or inconjunction with the foregoing, accelerometer 208 and GPS receiver 210may transmit data directly to non-volatile storage 206. In thisembodiment, CPU 202 may access the data (e.g., location and/or eventdata) from memory 204. In some embodiments, non-volatile storage 206 maycomprise a solid-state storage device (e.g., a “flash” storage device)or a traditional storage device (e.g., a hard disk). Specifically, GPSreceiver 210 may transmit location data (e.g., latitude, longitude,etc.) to CPU 202, memory 204, or non-volatile storage 206 in similarmanners. In some embodiments, CPU 202 may comprise a field programmablegate array or customized application-specific integrated circuit.

As illustrated in FIG. 2, the device 200 includes multiple networkinterfaces including cellular transceiver 212, wireless transceiver 214,and Bluetooth transceiver 216. As discussed in connection with FIG. 1,cellular transceiver 212 enables the device 200 to transmit event orlocation data, processed by CPU 202, to a server via a mobile or radionetwork. Additionally, CPU 202 may determine the format and contents ofdata transferred using cellular transceiver 212, wireless transceiver214, and Bluetooth transceiver 216 based upon detected networkconditions.

FIG. 3 is a logical block diagram illustrating a tracking device fordetecting the start of a walk event according to some embodiments of thedisclosure. As illustrated in FIG. 3, a device 300 includes a GPSreceiver 302, a geo-fence detector 304, an environment profiler 306,storage 308, CPU 310, and network interfaces 312.

In the illustrated embodiment, GPS receiver 302 records location dataassociated with the device 300 including numerous data pointsrepresenting the location of the device 300 as a function of time.

In one embodiment, geo-fence detector 304 stores details regarding knowngeo-fence zones. For example, geo-fence detector 304 may store aplurality of latitude and longitude points for a plurality of polygonalgeo-fences. In alternative embodiments, geo-fence detector 304 may storethe names of known Wi-Fi network SSIDs and associate each of the SSIDswith a geo-fence, as discussed in more detail with respect to FIGS. 4and 5. In one embodiment, geo-fence detector 304 may store, in additionto an SSID, one or more thresholds for determining when the device 300exits a geo-fence zone. Although illustrated as a separate component, insome embodiments, geo-fence detector 304 may be implemented within CPU310, for example, as a software module.

In one embodiment, GPS receiver 302 may transmit latitude and longitudedata to geo-fence detector 304 via storage 308 or, alternatively,indirectly to storage 308 via CPU 310. In these embodiment, geo-fencedetector 304 receives the latitude and longitude data representing thecurrent location of the device 300 and determines whether the device 300is within or has exited a geo-fence zone. If geo-fence detector 304determines that the device 300 has exited a geo-fence zone the geo-fencedetector 304 may transmit the notification to CPU 310 for furtherprocessing.

Alternatively, geo-fence detector 304 may query network interfaces 312to determine whether the device is connected to a Wi-Fi network. In thisembodiment, geo-fence detector 304 may compare the current Wi-Fi SSID(or lack thereof) to a list of known SSIDs. If geo-fence detector 304does not detect that the device 300 is currently connected to a knownSSID, geo-fence detector 304 may transmit a notification to CPU 310 thatthe device has exited a geo-fence zone. Alternatively, geo-fencedetector 304 may receive the strength of a Wi-Fi network and determinewhether the current strength of a Wi-Fi network is within apredetermined threshold as described more fully with respect to FIG. 4.

As illustrated in FIG. 3, device 300 further includes environmentprofiler 306. In one embodiment, environment profiler 306 stores pastwalk environment details regarding the environmental conditions whenprevious walk modes were enabled. For example, past walk environmentdetails may include the time of day, the location of the trackingdevice, movement data associated with the device (e.g., velocity,acceleration, etc.) for previous time a walk mode was enabled. Past walkenvironment details may additionally include a schedule of walks, alisting of responses to walk mode prompts, and other relevant details.In one embodiment, the environment profiler 306 may retrieve past walkenvironment details from local storage present on a tracking device.Alternatively, or in conjunction with the foregoing, environmentprofiler 306 may retrieve past walk environment details from a servervia network interfaces 312. Embodiments of methods performed byenvironment profiler 306 are described more fully with respect to FIG. 5and are not repeated herein for the sake of clarity. Althoughillustrated as a separate component, in some embodiments, environmentprofiler 306 may be implemented within CPU 310, for example, as asoftware module.

CPU 310 is capable of controlling access to storage 308, retrieving datafrom storage 308, and transmitting data to a networked device vianetwork interfaces 312. As discussed more fully with respect to FIGS. 4and 5, CPU 310 may receive indications of geo-fence zone exits fromgeo-fence detector 304 and may communicate with a mobile device usingnetwork interfaces 312. Additionally, CPU 310 may receive an indicationthat a walk mode should be enabled from environment profile 306 and mayenable a walk mode accordingly. In one embodiment, when a walk mode isenabled, CPU 310 may receive location data from GPS receiver 302 and maystore the location data in storage 308. In one embodiment, storinglocation data may comprise associated a timestamp with the data. In someembodiments, CPU 310 may retrieve location data from GPS receiver 302according to a pre-defined interval. In some embodiments, this intervalmay be dynamically changed based on the estimated length of a walk orthe remaining battery life of the device 300. CPU 310 may further becapable of transmitting location data to a remove device or location vianetwork interfaces 312.

FIG. 4 is a flow diagram illustrating a method for detecting the startof a walk event according to some embodiments of the disclosure.

In step 402, the method 400 monitors the location of a device. In oneembodiment, monitoring the location of a device may comprise monitoringthe GPS position of the device at regular intervals. For example, themethod 400 may poll a GPS receiver every five seconds and retrieve alatitude and longitude of a device. Alternatively, in some embodiments,continuous polling of a GPS location may significantly reduce thebattery life of the device. Thus, in these embodiments, the method 400may utilize other methods for estimating the position of the device. Inone embodiment, the method 400 may monitor the location of a device bydetermining whether the device is connected to a known Wi-Fi network andusing the connection to a Wi-Fi network as an estimate of the devicelocation. In alternative embodiments, a device may be paired to a mobiledevice via a Bluetooth network. In this embodiment, the method 400 mayquery the paired device to determine its location using, for example,the GPS coordinates of the mobile device.

In step 404, the method 400 determines whether the device has exited ageo-fence zone. As discussed previously, in one embodiment, the method400 may continuously poll a GPS receiver to determine the latitude andlongitude of a device. In this embodiment, the method 400 may thencompare the received latitude and longitude to a known geo-fence zone,wherein the geofenced region includes a set of latitude and longitudepoints defining a polygonal region. Alternatively, in the embodimentwhere the method 400 uses the presence of a Wi-Fi network as indicativeof a location, the method 400 may determine that a device exitsgeo-fence zone when the presence of a known Wi-Fi network is notdetected. For example, a tracking device may be configured to identify ahome network (e.g., using the SSID of the network). When the device ispresent within the home (e.g., when a pet is present within the home),the method 400 may determine that the device has not exited thegeo-fence zone. However, as the device moves out of range of the knownWi-Fi network, the method 400 may determine that a geo-fence zone hasbeen exited, thus implicitly constructing a geo-fence zone based on thecontours of the Wi-Fi network.

Alternatively, or in conjunction with the foregoing, the method 400 mayemploy a continuous detection method to determine whether a device exitsa geo-fence zone. Specifically, Wi-Fi networks generally degrade insignal strength the further a receiver is from the wireless accesspoint. In one embodiment, the method 400 may receive the signal strengthof a known Wi-Fi network from a wireless transceiver. In thisembodiment, the method 400 may set one or more predefined thresholds todetermine whether a device exits geo-fence.

For example, a hypothetical Wi-Fi network may have signal strengthsbetween ten (strongest) and zero (absence). In a first embodiment, themethod 400 may simply monitor for a signal strength of zero beforedetermining that a device exited a geo-fence zone. Alternatively, or inconjunction with the foregoing, the method 400 may set a thresholdsignal strength value of three as defining a beacon zone (i.e., signalstrength between 3 and 10) and implicitly setting a second threshold(i.e., between 0 and 3) as the border of a geo-fence region. In thisexample, the method 400 may determine a device exited a geo-fence whenthe signal strength of a Wi-Fi network drops below a value of three. Insome embodiments, the method 400 may utilize a timer to allow for thepossibility of the Wi-Fi signal strength returning above the predefinedthreshold. In this embodiment, the method 400 allows for temporarydisruptions in Wi-Fi signal strength and avoids false positives.

If the method 400 determines that a device has not exited a geo-fencezone, the method 400 continues to monitor the device location in step402. Alternatively, if the method 400 determines that a device hasexited a geo-fence zone, the method 400 prompts a user to confirm that awalk mode should be enabled in step 406. In one embodiment, promptingfor a walk mode confirmation may additionally include determiningwhether the device is with a known user, as described more fully withrespect to FIG. 5.

In one embodiment, prompting a user to confirm a walk mode may comprisenotifying a user's mobile device. For example, a tracking device may bepaired with a mobile device via a Bluetooth connection. In thisembodiment, the method 400 may comprise alerting the device via theBluetooth connection that a walk mode has been detected and allowing theuser to confirm the same (e.g., by providing an on-screen notification).Alternatively, a user may be notified by receiving a notification from aserver, the notification generated based on the tracking devicecommunicating the detection of a walk mode to said server.

In alternative embodiments, the method 400 may bypass step 406 and inferthe start of a walk mode using various techniques. In one embodiment,the method 400 may identify the presence of a known device associatedwith walk modes. For example, the method 400 may detect the presence ofa device carried by a dog walker and thus may infer that a walk mode hasstarted when the device and the dog walker's device simultaneously exita geo-fence region.

Alternatively, or in conjunction with the foregoing, the method 400 mayinfer the start of a walk based on the time of day. For example, a usermay schedule walks at certain times during the day (e.g., morning,afternoon, or night). As part of detecting whether a device exited ageo-fence zone, the method 400 may further inspect a schedule of knownwalks to determine whether the timing of the geo-fence exiting occurredat an expected walk time (or within an acceptable deviation therefrom).

Alternatively, or in conjunction with the foregoing, the method 400 mayemploy machine-learning techniques to infer the start of a walk withoutrequiring the above input from a user. For example, during the first fewinstances of detecting a walk mode, the method 400 may continue toprompt the user to confirm that a walk mode has begun. As the method 400receives input from users confirming or denying a walk mode has begun,the method 400 may train a learning machine to identify conditionsassociated with walks. For example, after a few prompt confirmations,the method 400 may determine that on weekdays between 7:00 AM and 7:30AM, a tracking device repeatedly enables a walk mode (i.e., conformingto a morning walk of a pet). Relatedly, the method 400 may learn thatthe same event (e.g., a morning walk) may occur later on weekends (e.g.,between 8:00 AM and 8:30 AM).

In this manner, the method 400 may bypass an explicit prompting of theuser and may simply presume a walk mode has been confirmed. In thisembodiment, the method 400 may allow a user to disable a walk mode orretroactively cancel a walk mode to further refine the automaticdetection of a walk mode.

If the user does not confirm that a walk mode should be enabled, themethod 400 may continue to monitor the device location in step 402.Alternatively, if the user does confirm that a walk mode should beenabled, the method 400 begins to record the GPS location of the devicein step 410.

In one embodiment, the method 400 may continuously poll the GPS locationof a device to provide multiple “breadcrumbs” that a device encounterswhile a walk mode is enabled. In some embodiments, a poll interval of aGPS device may be adjusted based on the battery level of the device. Inalternative embodiments, the poll interval may be adjusted based on theexpected length of the walk mode. That is, if a walk mode is expected tolast for thirty minutes (e.g., while walking a dog), the method 400 maycalculate, based on battery life, the optimal poll interval. Asdiscussed above, the length of a walk may be input manually by a user ormay be determining using a machine-learning algorithm based on previouswalks.

In step 412, the method 400 transmits location details. In oneembodiment, the method 400 continuously transmits GPS location detailsto a server while a walk mode is enabled. As discussed above, the method400 may utilize a poll interval to determine how frequently to senddata. In one embodiment, the method 400 may transmit location data usinga cellular or other radio network. Methods for transmitting locationdata over cellular networks are described more fully in commonly ownedU.S. Non-Provisional application Ser. No. 15/287,544, entitled “Systemand Method for Compressing High Fidelity Motion Data for TransmissionOver a Limited Bandwidth Network,” which is hereby incorporated byreference herein in its entirety.

Finally, the method 400 determines whether a walk has ended, step 414.If so, the method 400 returns to monitoring the location of the device.If not, the method 400 continues to record the GPS location of thedevice.

In one embodiment, the method 400 may determine that a walk mode hasended by detecting, using the GPS location of the device, that thedevice has re-entered a geo-fence zone, as discussed previously.Alternatively, or in conjunction with the foregoing, the method 400 maydetermine a walk mode has ended by detecting the presence of a knownWi-Fi network as discussed previously. Alternatively, or in conjunctionwith the foregoing, the method 400 may receive a notification from auser that a walk mode has ended.

FIG. 5 is a flow diagram illustrating a method for confirming the startof a walk event according to some embodiments of the disclosure.

In step 502, the method 500 detects whether a device has exited ageo-fence zone. Detecting an exit from a geo-fence zone is discussed inmore detail with respect to FIG. 4 and is not repeated herein for thesake of clarity.

In step 504, the method 500 identifies a mobile device. In oneembodiment, identifying a mobile device may comprise identifying amobile device connected to a tracking device via a Bluetooth network.For example, upon detecting a geo-fence exit, the method 500 scans fordevices within range of a Bluetooth network to identify known devices(e.g., devices previously paired with the tracking device).Alternatively, or in conjunction with the foregoing, the method 500 mayidentify a mobile device by determining whether a known device isconnected to a network, such as the Internet. In this embodiment, themethod 500 may transmit a notification to a server via a cellularnetwork. The server may, in turn, identify if any known devices arecapable of receiving communications from the server (e.g., are“online”). In this manner, the method 500 may identify known deviceswithout a short-range wireless network and may identify devices remotefrom the tracking device. For example, the method 500 may identify thepet owner who is currently remote from a pet equipped with a trackingdevice (e.g., an owner who is at work). In this manner, the method 500may allow an owner (or account administrator) to control whether a walkmode should be enabled. Alternatively, using a local network (e.g.,Bluetooth) enables the person closest to the device to enable a walkmode. In some embodiments, both techniques may be utilized incombination to validate each other.

If a device is found (step 506), the method 500 confirms the deviceidentity, step 508.

As discussed previously, confirming the identity of a device maycomprise identifying a known device present on a Bluetooth network. Forexample, the method 500 may query for known devices associated with petwalkers, owners, etc. In this embodiment, the method 500 may confirm theidentity of a device by determining that the device has previously beenpaired with a tracking device. Alternatively, the method 500 mayactively request that the device confirm its identity (e.g., via anotification or prompt). In alternative embodiments, the method 500 mayverify the identity by detecting that the device corresponds to a knowndevice based on the time of day. For example, the method 500 may beaware that a walk mode is regularly enabled at a specific time of day(as discussed previously), and may automatically verify the identity ofa device if a device is detected at, or around, that time.

If the method 500 confirms the identity of the device, step 510, themethod 500 prompts the user to enable a walk mode, step 512. Embodimentsdescribing the implementation of a walk mode are discussed more fullywith respect to FIG. 4 and are not repeated herein for the sake ofclarity. As discussed herein, the method 500 may alternatively skipprompting for a walk mode in step 512 if it can predicatively determinethat a walk mode should be enabled. For example, the method 500 maystore a list of known devices and times associated with past walks andmay predicatively determine that the confirmation of the identity of aknown device at a specific time should automatically trigger a walkmode. In some embodiments, the method 500, upon automatically detectinga walk mode, may allow the owner of the device to disable a walk mode ifthe method 500 errantly detects a walk mode automatically.

If the method 500 does not identify a mobile device (step 506) or themethod 500 cannot confirm the identity of a mobile device (step 510),the method 500 may infer that a walk mode should be enabled asillustrated in steps 514 through 520.

In step 514, the method 500 retrieves current environment details.

In the illustrated embodiment, current environment details may includedata regarding the state of the tracking device when a geo-fence exitevent occurs. For example, current environment details may include thetime of day, the location of the tracking device, movement dataassociated with the device (e.g., velocity, acceleration, etc.).Although illustrated in the alternative, current environment details mayadditionally be collected if a device is found in step 506, or anidentity is confirmed in step 510. As discussed previously, steps 514through 518 may be executed despite these confirmations to improve theaccuracy of the method 500.

In step 516, the method 500 retrieves past walk environment details.

In the illustrated embodiment, past walk environment details may includethe same data as current environment details (e.g., time, location,movement, etc.) with respect to past walk events and/or may includedetails regarding future (i.e., scheduled events). For example, pastwalk environment details may additionally include a schedule of walks, alisting of responses to walk mode prompts (e.g., those collected in step406 of FIG. 4), and other relevant details. In one embodiment, themethod 500 may retrieve past walk environment details from local storagepresent on a tracking device. In alternative embodiments, the method 500may retrieve past walk environment details from a server via a cellularor Wi-Fi connection.

In step 518, the method 500 determines if there is a match between thecurrent environment detail and past walk environment details.

In the illustrated embodiment, the method 500 may compare the currentdetails (e.g., time of day) to past, known walks to infer whether a walkmode should be enabled, and implicitly that a walk is taking place. Forexample, past walk environment details may include consistent dataindicating that a walk often takes place on weekdays at noon. In oneembodiment, the method 500 compares the current environment details(e.g., time of day, day of week) to the recorded past walk environmentdetails and determines that since the current date and time correspondsto a known, historical walk schedule, a walk is occurring. In someembodiments, the method 500 may compute a binary answer to suchcomparisons. In alternative embodiments, the method 500 may calculate aprobabilistic value indicating the likelihood of a walk occurring.

In alternative embodiments, the method 500 may employ machine-learningtechniques to generate a predictive function to determine whether a walkis occurring based on current environment details. In one embodiment,the method 500 may generate such a function locally, while inalternative embodiments, the method 500 may retrieve the function (orthe results thereof) from a remote data source (e.g., a server). In someembodiments, the method 500 may utilize a decision tree or similarmechanism to determine that a walk is occurring probabilistically. Asdiscussed previously, these machine-learning techniques may be refinedusing manual prompts of the user. In alternative embodiments, the method500 may additionally use inputs from other devices to refine thepredictive function.

If the method 500 determines a match exists, step 518, the method 500enables a walk mode (step 512), as discussed previously. If not, themethod 500 optionally issues an alert that a tracking device exited ageo-fence zone.

As illustrated in FIG. 5, the method 500 may reach step 520 afterexhausting all, or substantially all, means for determining whether awalk has begun. Nevertheless, the method 500 has previously detectedthat a tracking device has exited a geo-fence zone. In this embodiment,the method 500 may determine, for example, that an animal equipped witha tracking device, has strayed from a geo-fence zone on its volition. Inthis embodiment, the method 500 may alert a user (e.g., an owner) thatthe animal equipped with the tracking device may potentially be strayingfrom a desired, geo-fenced zone. In some embodiments, the method 500 mayadditionally provide a prompt to the user allowing the user to confirmthat a walk mode should not be occurring. As discussed previously, themethod 500 may store this response and incorporate the response as partof the past walk environment details used in steps 516 and 518.

For the purposes of this disclosure a module is a software, hardware, orfirmware (or combinations thereof) system, process or functionality, orcomponent thereof, that performs or facilitates the processes, features,and/or functions described herein (with or without human interaction oraugmentation). A module can include sub-modules. Software components ofa module may be stored on a computer readable medium for execution by aprocessor. Modules may be integral to one or more servers, or be loadedand executed by one or more servers. One or more modules may be groupedinto an engine or an application.

For the purposes of this disclosure the term “user”, “subscriber”“consumer” or “customer” should be understood to refer to a user of anapplication or applications as described herein and/or a consumer ofdata supplied by a data provider. By way of example, and not limitation,the term “user” or “subscriber” can refer to a person who receives dataprovided by the data or service provider over the Internet in a browsersession, or can refer to an automated software application whichreceives the data and stores or processes the data.

Those skilled in the art will recognize that the methods and systems ofthe present disclosure may be implemented in many manners and as suchare not to be limited by the foregoing exemplary embodiments andexamples. In other words, functional elements being performed by singleor multiple components, in various combinations of hardware and softwareor firmware, and individual functions, may be distributed among softwareapplications at either the client level or server level or both. In thisregard, any number of the features of the different embodimentsdescribed herein may be combined into single or multiple embodiments,and alternate embodiments having fewer than, or more than, all of thefeatures described herein are possible.

Functionality may also be, in whole or in part, distributed amongmultiple components, in manners now known or to become known. Thus,myriad software/hardware/firmware combinations are possible in achievingthe functions, features, interfaces and preferences described herein.Moreover, the scope of the present disclosure covers conventionallyknown manners for carrying out the described features and functions andinterfaces, as well as those variations and modifications that may bemade to the hardware or software or firmware components described hereinas would be understood by those skilled in the art now and hereafter.

Furthermore, the embodiments of methods presented and described asflowcharts in this disclosure are provided by way of example to providea more complete understanding of the technology. The disclosed methodsare not limited to the operations and logical flow presented herein.Alternative embodiments are contemplated in which the order of thevarious operations is altered and in which sub-operations described asbeing part of a larger operation are performed independently.

While various embodiments have been described for purposes of thisdisclosure, such embodiments should not be deemed to limit the teachingof this disclosure to those embodiments. Various changes andmodifications may be made to the elements and operations described aboveto obtain a result that remains within the scope of the systems andprocesses described in this disclosure.

What is claimed is:
 1. A method comprising: detecting that a wearabledevice is in a walk mode if it is determined that the wearable devicehas exited a geo-fence zone and that the wearable device is notconnected to a wireless network; comparing current environment detailsassociated with the wearable device to past walk environment detailsassociated with the wearable device to identify at least one similaritybetween the current environment details and the past walk environmentdetails; confirming that the wearable device is in the walk mode uponidentifying at least one similarity between the current environmentdetails and the past walk environment details using a predictivefunction, the predictive function refined using the one or more previousresponses to a walk mode prompt; and transmitting a recorded GPSlocation of the wearable device while the wearable device is in a walkmode.
 2. The method according to claim 1, further comprising:identifying the location of the wearable device; and determining thatthe wearable device has exited a geo-fence zone by comparing thelocation to a plurality of latitude and longitude points defining apolygonal region representing the geo-fence zone.
 3. The methodaccording to claim 2 wherein identifying the location of a wearabledevice comprises: identifying an active wireless network to which thewearable device is currently connected; identifying a list of knownwireless networks; and determining if the active wireless network is inthe list of known wireless networks.
 4. The method according to claim 3wherein determining if the wearable device has exited a geo-fence zonecomprises detecting that the wearable device has disconnected from theactive wireless network.
 5. The method according to claim 1 whereinconfirming that a wearable device is in a walk mode further comprisesprompting a user for confirmation that a wearable device is in a walkmode.
 6. The method according to claim 1 wherein confirming that awearable device is in a walk mode further comprises detecting thepresence of a known device within a predefined proximity to the wearabledevice and confirming the identity of the known device.
 7. The methodaccording to claim 1 wherein the environment details include at leastone of the date, the time, the location of past walks, a list ofscheduled walks, and one or more previous responses to a walk modeprompt.
 8. The method according to claim 1 wherein the currentenvironment details include the date and time it is determined that thedevice has exited a geo-fence zone and the location of the wearabledevice.
 9. The method according to claim 1 wherein confirming that awearable device is in a walk mode further comprises confirming that awearable device in a walk mode without confirmation of a user.
 10. Themethod according to claim 1 further comprising alerting a user that thewearable device has exited a geo-fence zone if it is not confirmed thata wearable device is in a walk mode.
 11. An apparatus comprising: aprocessor; and a storage medium for tangibly storing thereon programlogic for execution by the processor, the stored program logiccomprising: logic, executed by the processor, for detecting that awearable device is in a walk mode if it is determined that the wearabledevice has exited a geo-fence zone and that the wearable device is notconnected to a wireless network; logic, executed by the processor, forcomparing current environment details associated with the wearabledevice to past walk environment details associated with the wearabledevice to identify at least one similarity between the currentenvironment details and the past walk environment details; logic,executed by the processor, for confirming that the wearable device is inthe walk mode upon identifying at least one similarity between thecurrent environment details and the past walk environment details usinga predictive function, the predictive function refined using the one ormore previous responses to a walk mode prompt; and logic, executed bythe processor, for transmitting a recorded GPS location of the wearabledevice while the wearable device is in a walk mode.
 12. The apparatusaccording to claim 11, the stored program logic further comprising:logic, executed by the processor, for identifying the location of thewearable device; and logic, executed by the processor, for determiningthat the wearable device has exited a geo-fence zone by comparing thelocation to a plurality of latitude and longitude points defining apolygonal region representing the geo-fence zone.
 13. The apparatusaccording to claim 12 wherein identifying the location of a wearabledevice comprises: identifying an active wireless network to which thewearable device is currently connected; identifying a list of knownwireless networks; and determining if the active wireless network is inthe list of known wireless networks.
 14. The apparatus according toclaim 13 wherein determining if the wearable device has exited ageo-fence zone comprises detecting that the wearable device hasdisconnected from the active wireless network.
 15. The apparatusaccording to claim 11 wherein confirming that a wearable device is in awalk mode further comprises prompting a user for confirmation that awearable device is in a walk mode.
 16. The apparatus according to claim11 wherein confirming that a wearable device is in a walk mode furthercomprises detecting the presence of a known device within a predefinedproximity to the wearable device and confirming the identity of theknown device.
 17. The apparatus according to claim 11 wherein theenvironment details include at least one of the date, the time, thelocation of past walks, a list of scheduled walks, and one or moreprevious responses to a walk mode prompt.
 18. The apparatus according toclaim 11 wherein the current environment details include the date andtime it is determined that the device has exited a geo-fence zone andthe location of the wearable device.
 19. The apparatus according toclaim 11 wherein confirming that a wearable device is in a walk modefurther comprises confirming that a wearable device in a walk modewithout confirmation of a user.
 20. The apparatus according to claim 11the stored program logic further comprising logic, executed by theprocessor, for alerting a user that the wearable device has exited ageo-fence zone if it is not confirmed that a wearable device is in awalk mode.